How To Fund Legal AI Start-Ups: From Bitcoins to Venture Capital

You get together a great team, some of whom hopefully have first hand experience of the problem you want to solve; you get the product to a workable level, maybe partner with some friendly proto-client while you test things out, maybe get a little bit of seed funding to tide things over; then you go to the people with the big money and receive a huge dollop of lovely money; plough the cash into BD and more staff and go large with the motto: ‘Scale! Scale! Scale!’ ….Rinse and repeat the final step, then eventually sell and everyone’s a millionaire. That’s what you want to do…right?

…or do you? Maybe the classic start-up pathway is not the only way, especially so for legal AI and other New Wave legal tech companies? Here’s a couple of thoughts.

It’s Not What You Do, But the Way that You Do It

In the last couple of days a smart contract start-up (which also offers an AI assistant) has raised 5,098 Bitcoins’ worth of capital, which is approximately $11,134,732, by selling its own digital currency or ‘token’ on the open market via an ICO (an Initial Coin Offering). That token is called DELTA.

Yep, you read that correctly, that’s $11.1m raised by selling little digital blocks of IOUs in a company that many even in the legal tech world have not heard of yet.

That company is Estonia-based, Agrello, which Artificial Lawyer wrote about earlier this week and which is making an entirely new platform for the creation, use and management of legally binding smart contracts. They are even chucking in an AI assistant to help users.

It’s all a very compelling package, but what is especially striking is the way they have avoided the need to gain traditional external investment, at least in the form of handing over a big chunk of equity to a VC fund, or even a law firm that wants to dabble with legal tech ownership and development and fancies a piece of legal AI action.

After ruminating on the meaning of the legal tech ICO, I couldn’t help but think back to just the week before when I was at the culmination of MDR LAB’s accelerator programme for start-ups.

MDR LAB was set up by UK law firm Mishcon de Reya and helped a group of start-ups, several in the legal tech space including one Contracting Automation Tool (CAT) and one legal AI doc review system, to learn more about the needs of a large commercial law firm and to work with them to improve their product. Likewise the lawyers at the firm learnt a lot about this new wave of legal tech and other types of application. It was a real win-win.

One of the key themes that was headlined by the initial speaker on the ‘graduation day’ was from a retail tech company that had already secured a tonne of funding. That theme was: money and how they eventually got it. They weren’t part of the accelerator, but had been invited to give their perspective. And, the announcement they had just received millions of dollars in funding from investors received a fist-pumping cheer from the audience.

It was also clear that the now nicely funded start-up was going to grow fast and scale. But, then, everybody buys clothes, the market is gigantic, expectations of rapid scaling make a lot of sense in that sector. (Although it was interesting to note that the company had found it hard to get the right backing in UK/Europe and instead had found the pot of gold in Asia, where fashion companies want to throw cash at retail start-ups. Their funding journey had actually been quite tortuous and long.)

When the MDR LAB start-ups were giving their presentations they naturally did not mention the need for capital, they just did their pitches. But, one could not help but feel sitting in the audience there a bit like a VC partner at a beauty parade of potential investment targets.

And in fact, MDR is holding open the option that it could invest in the start-ups, though perhaps of more immediate importance to the entrepreneurs is using the law firm for more Beta testing and to gain another paying client, plus that all important credibility that comes from being used by lawyers in a well known commercial firm. I.e. although it felt like the sub-text was all about the money, the reality was that learning from hands-on experience with a law firm and gaining some kudos that would reassure other potential clients may have been the bigger prize.

The reason why the non-money bits seemed so important was that legal AI and other new legal tech products are entering a market that is not super-instantly-scalable, even if the legal market is worth $800bn globally. The reality is that we are still at the start of the adoption curve for legal AI and other tech like smart contracts. Refining the product so its super credible and ‘robust’ (as Luminance-backer Mike Lynch puts it) and winning renown that allows you to sell to new clients, just seems the more important issue right now.

The final bit of the mental jigsaw was considering that two of the biggest names in legal AI were primarily self-funded (there are many others, but these two serve as a good example). RAVN, up to its merger with iManage this year was still largely held by its original founders. Meanwhile Kira Systemsremains very much in the hands of its founders too.

Funding themselves didn’t stop these two from doing very well. And if they had been given a huge dollop of cash very early on, would it have helped? Back when the founders were just setting up their own companies the market for legal AI was anaemic and probably having $10m extra in the company bank account may not have made much difference, especially if the client base was not ready to adopt this tech.

The reality is these companies slowly and steadily improved their tech, especially around the use of natural language processing (NLP) for legal clause detection and analysis. A tonne of cash may not have made much difference there. R&D takes time. It takes money too, for sure, but most of all it takes time and many experiments and iterations. So, taking it slow really helped these companies to develop the products they wanted to bring to market before seeking to scale, often working with partners over a long period to learn and improve. And you cannot scale if haven’t got a ‘robust’ product. QED, big stacks of cash up front is not always the best route.

Three Funding Routes

So, what can we learn from these three different approaches:

the coin-funded ‘millionaires overnight’ approach

the start-up that really wants funding so it can grow and scale ASAP

the start-up that went slow and steady and funded itself

The Agrello approach of using its own tokens is ingenious as it is creating value out of a concept that is still developing. Yet it works because they’ve made the use of tokens integral to the operation of their platform (see story) in part because it has a blockchain dimension.

A legal AI doc review company, for example, would find it a bit harder to develop a business case for its own token sale/ICO to underscore their growth. Unless the digital currency has some specific use case integral to the doc review process then it seems unlikely to be a currency that will hold value. I.e. there would not be a liquid market for the exchange of the tokens.

Fundamental to the success of any digital currency is the ability to grow the market for the exchange of that currency. Bitcoin did this, most of the hundreds of other cryptocurrencies out there have not. Agrello has been clever here by making the growth of its platform in turn support the growth of DELTA exchange and use.

That said, even Agrello’s ICO does have some risks. If the start-up doesn’t take off then the integral use of the tokens, DELTAs, may be a moot point. Then people may have paid for a currency that is no longer of much use and hence of little value. Although, presumably the Bitcoins that the DELTAs were bought with recently will still be holding their value.

Conclusion: although an ICO for a legal tech start-up sounds exciting we may not see that many, as platforms need to integrate the token into their use case and few legal AI applications will do that.

The ‘give me the money and let me scale ASAP’ approach favoured by those approaching the VC community sounds a lot more, er, ‘traditional’. Therefore it should be a lot more applicable to legal AI companies…right?

The answer is yes and no. Start-ups need cash just to keep going even at the earliest stages, so clearly funds have to come from somewhere and not everyone has a big savings account gained from their previous job or a rich uncle to help support a project. While some partners are willing to pay you while you train up the system and iron out problems, some are not, or at least not enough. Hence, some external funding does seem a logical step for many.

That said cash won’t make your co-founders and all important CTO any smarter. It won’t make your NLP any more sophisticated. It won’t make your unique idea any better or create a niche for you that others are not already in. All that comes with your original DNA as a start-up and as a team of entrepreneurs and legal tech pioneers. Money can’t buy that. But cash will allow you to:

Hire staff, from coders to spread the load, to business development and marketing teams to professional managers such as COOs and the like. In short, the cash will help you to become more of a true corporate with the functions and better division of labour that larger companies have.

The cash will allow you to expand into new physical locations and fund marketing and sales trips, events and content production. And the more paying customers you can bring on board via this approach the more you can keep growing (if the application is loved by clients….).

Stop having to live hand to mouth and the founders can pay themselves a proper salary, rather than holding every penny back to keep the dream alive.

Can help with buying time to test and iterate and improve the tech. Though, funders can get a bit nervous if you are still testing after five years and haven’t built a potential pipeline of proper paying clients.

Conclusion: the fundamental start-up challenge with legal AI systems is that although it should in theory be massively scalable as a technology, i.e. every law firm should be making use of the wide array of today’s legal AI systems, the reality is that the market remains small, for now, though that will change. That said, if you don’t go ICO, which most won’t, and you don’t have the time companies such as RAVN had to perfect their tech in what is now a very different market for AI since they first launched seven years ago, then going for external funding seems to be the most sensible route. What is different is the traditional path of product, pitch, money, scale, may not fit quite so well with legal AI. It’s just going to be a bit slower here.

The investment funds out there I’ve met seem fascinated by the legal AI world. They see legal as a massive sector that is ripe for change and generally agree that the use of AI and better data analytics will be a game changer. It’s just that they want it to happen yesterday and not wait.

But, the ‘AI-ization’ of the legal market is going to be an incremental phenomenon. We may reach a watershed moment in a few years and thereafter everyone is using at least three or four different types of AI system across the firm, or inhouse. But we are not there yet. Although I do believe we will get there.

Big funds want you to scale – and naturally so, otherwise why did they bother to fund you? They can do this with consumer tech/retail tech applications. With tech designed to help the esoteric world of commercial lawyers things are a little more tricky. While companies such as Luminance have been collecting new clients at incredible speed, they are more the exception than the rule. Making use of its tent pole client, Slaughter and May’s own connections in the legal world has certainly helped. Having a billionaire standing behind them also helps to overcome money worries. I.e. Luminance is not like most other legal AI start-ups that are under a year old.

This then raises another challenge. While it’s hard for most to grow super fast as a new legal AI start-up, you’re also entering a market with far more players. What happens now that legal AI tech is sprouting up all over the world (for example there are now two legal AI co.s in India, China is on the verge of moving into legal AI also and North America and Europe are teeming with legal AI applications)?

This is not a quiet market any longer. Now everyone is jostling for a place at the legal AI table, to get heard, to get seen, to develop solid client relationships. In short, legal AI is fast becoming a vibrant and very real market all of its own. Yet, at the same time it’s still a hard sell. Law firms and corporates are not buying legal AI products in the same way, for example, as when law firms leaped at the use of the internet or digital word processing in the 1990s.

This all means that choosing your growth strategy is incredibly important. Seven years ago legal AI companies had time to kill. Today they may not have the luxury of time. Seven years ago the number of viable legal AI companies could be counted on one hand. Now they are popping up every few weeks. Different times require different strategies. Getting the right strategy for your legal tech company is therefore vital.